Cover Image

Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yamaguchi, Shin'ya, Kanai, Sekitoshi, Adachi, Kazuki, Chijiwa, Daiki
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computer Vision and Pattern Recognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Post-pre-training for Modality Alignment in Vision-Language Foundation Models
by: Yamaguchi, Shin'ya, et al.
Published: (2025)

Learning Robust Convolutional Neural Networks with Relevant Feature Focusing via Explanations
by: Adachi, Kazuki, et al.
Published: (2022)

Rationale-Enhanced Decoding for Multi-modal Chain-of-Thought
by: Yamaguchi, Shin'ya, et al.
Published: (2025)

Zero-shot Concept Bottleneck Models
by: Yamaguchi, Shin'ya, et al.
Published: (2025)

Parallel In-context Learning for Large Vision Language Models
by: Yamaguchi, Shin'ya, et al.
Published: (2026)

Transfer Learning with Pre-trained Conditional Generative Models
by: Yamaguchi, Shin'ya, et al.
Published: (2022)

Evaluating Time-Series Training Dataset through Lens of Spectrum in Deep State Space Models
by: Kanai, Sekitoshi, et al.
Published: (2024)

Explanation Bottleneck Models
by: Yamaguchi, Shin'ya, et al.
Published: (2024)

MultiModal Fine-tuning with Synthetic Captions
by: Enomoto, Shohei, et al.
Published: (2026)

Uniformity First: Uniformity-aware Test-time Adaptation of Vision-language Models against Image Corruption
by: Adachi, Kazuki, et al.
Published: (2025)

Toward Data Efficient Model Merging between Different Datasets without Performance Degradation
by: Yamada, Masanori, et al.
Published: (2023)

Difference Vector Equalization for Robust Fine-tuning of Vision-Language Models
by: Suzuki, Satoshi, et al.
Published: (2025)

Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift
by: Adachi, Kazuki, et al.
Published: (2024)

Understanding Pure Textual Reasoning for Blind Image Quality Assessment
by: Li, Yuan, et al.
Published: (2026)

Test-time Adaptation for Regression by Subspace Alignment
by: Adachi, Kazuki, et al.
Published: (2024)

Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching
by: Enomoto, Shohei, et al.
Published: (2024)

Machine Learning Modeling for Multi-order Human Visual Motion Processing
by: Sun, Zitang, et al.
Published: (2025)

Towards the Resistance of Neural Network Watermarking to Fine-tuning
by: Tang, Ling, et al.
Published: (2025)

Regularizing Neural Network Training via Identity-wise Discriminative Feature Suppression
by: Chapman, Avraham, et al.
Published: (2022)

Exploring Diffusion Models' Corruption Stage in Few-Shot Fine-tuning and Mitigating with Bayesian Neural Networks
by: Wu, Xiaoyu, et al.
Published: (2024)

Automatic Extraction of Road Networks by using Teacher-Student Adaptive Structural Deep Belief Network and Its Application to Landslide Disaster
by: Kamada, Shin, et al.
Published: (2025)

PerNodeDrop: A Method Balancing Specialized Subnets and Regularization in Deep Neural Networks
by: Omathil, Gelesh G, et al.
Published: (2025)

Lossless Vocabulary Reduction for Auto-Regressive Language Models
by: Chijiwa, Daiki, et al.
Published: (2025)

Neural Redshift: Random Networks are not Random Functions
by: Teney, Damien, et al.
Published: (2024)

Enhancing Fine-Grained Visual Recognition in the Low-Data Regime Through Feature Magnitude Regularization
by: Chapman, Avraham, et al.
Published: (2024)

Improved Regularization and Robustness for Fine-tuning in Neural Networks
by: Li, Dongyue, et al.
Published: (2021)

Confidence-aware Denoised Fine-tuning of Off-the-shelf Models for Certified Robustness
by: Jang, Suhyeok, et al.
Published: (2024)

Multi-Modal Parameter-Efficient Fine-tuning via Graph Neural Network
by: Cheng, Bin, et al.
Published: (2024)

Pre-Trained Model Recommendation for Downstream Fine-tuning
by: Bai, Jiameng, et al.
Published: (2024)

Guiding Perception-Reasoning Closer to Human in Blind Image Quality Assessment
by: Li, Yuan, et al.
Published: (2025)

LoCO: Low-rank Compositional Rotation Fine-tuning
by: Nguyen, An, et al.
Published: (2026)

Fine-tuning CLIP Text Encoders with Two-step Paraphrasing
by: Kim, Hyunjae, et al.
Published: (2024)

Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning
by: Sehanobish, Arijit, et al.
Published: (2024)

Covariance-aware Feature Alignment with Pre-computed Source Statistics for Test-time Adaptation to Multiple Image Corruptions
by: Adachi, Kazuki, et al.
Published: (2022)

HAPI: A Model for Learning Robot Facial Expressions from Human Preferences
by: Yang, Dongsheng, et al.
Published: (2025)

Implicit to Explicit Entropy Regularization: Benchmarking ViT Fine-tuning under Noisy Labels
by: Marrium, Maria, et al.
Published: (2024)

Dynamic Dropout: Leveraging Conway's Game of Life for Neural Networks Regularization
by: Freire-Obregón, David, et al.
Published: (2025)

See Further for Parameter Efficient Fine-tuning by Standing on the Shoulders of Decomposition
by: Si, Chongjie, et al.
Published: (2024)

Connecting the Dots: Collaborative Fine-tuning for Black-Box Vision-Language Models
by: Wang, Zhengbo, et al.
Published: (2024)

SLCA++: Unleash the Power of Sequential Fine-tuning for Continual Learning with Pre-training
by: Zhang, Gengwei, et al.
Published: (2024)